Big Data, Big Biology, and the ‘Tipping Point’ in Quantified Health: Takeaways from Xconomy’s On-the-Record Dinner

Xconomy San Diego — 

Two of the biggest trends in technology innovation are converging—and as they come together, there is a chance to accomplish something rare in San Diego. Something exponential.

One of these forces is “big data,” the ever-increasing capabilities of computers and analytic software to move from gigabytes to terabytes, petabytes, and beyond. The other is “big biology,” which encompasses a breathtaking array of fundamental breakthroughs in DNA sequencing, molecular diagnostics, genome biology, proteomics, and other “omics” technologies.

Each is an irresistible force in its own right, and they are coming together like tributaries at the confluence of “quantified health,” a new field with the potential to fundamentally change health care. What makes this combination so powerful is the sheer magnitude of ways that “health” can now be measured—and in the use of data analytics to mine information that was previously unattainable.

The new tools of molecular biology are making it much more practical to analyze a patient’s genome—to determine if a patient has a genetic predisposition, say, for diabetes or heart disease. Advances in molecular diagnostics are also making it easier to regularly measure the hundreds of thousands of molecule-size constituents that are produced through genetic activity. With data analytics, it’s feasible to compare and chart these millions of data points over time to detect early signs of disease long before any symptoms appear—or to compare the data from one patient with the data from millions of other patients to see how they compare on the bell curve of “normal.”

This combination of big biology with big data has already begun—and leads to what Lee Hood of the Seattle-based Institute for Systems Biology calls “P4 Medicine”—health care that is predictive, preventive, personalized, and participatory. It is one reason why Larry Smarr, founding director of the California Institute for Telecommunications and Information Technology (Calit2), has become a de facto evangelist for quantified health.

Larry Smarr

“Never in human history has something that is critical to human health gone down in cost by a factor of 1 million in a decade the way genomics has,” says Smarr, who is also a San Diego Xconomist. Combine this megatrend with advances in sensors and related technologies that are embedded in current-generation smart phones—-and the plummeting costs of data storage and cloud computing—and you have all the needed ingredients for a technology revolution in health care.

With Smarr’s help, Xconomy brought together some of the best minds in business, life sciences, and information technology for an “on-the-record” dinner discussion about the implications of quantified health, and what it might take to harness the power of this new river of information.

“The decade we are now moving into is going to be radically different than [anything] in the history of health and medicine because of these exponential changes we’re going through,” Smarr says.

As we’ve reported previously, Smarr has used some of these new diagnostic tools to calibrate his own health, along with a variety of innovative devices that measure his physical activity, caloric burn, and sleep efficiency. Along the way, he’s become something of a poster child for quantified health (also known as “quantified self”), and he sometimes talks as if he’s getting more speaking requests than he can count.

Diego Miralles

What’s important, though, is that Smarr contends that San Diego already has all the pieces needed to become “one of the real leaders in quantified health.” He sees plenty of expertise here in genomics, molecular diagnostics, high-performance computing, wireless technologies, health IT, and data analytics. Yet these are only the ingredients. They still need to fit together, and San Diego still needs to muster the business and technology leadership to put the pieces together.

So what would it take to accomplish that here? This was one of the primary themes of our discussion.

“We are 3 million people,” says Diego Miralles, who heads Janssen Healthcare Innovation, an entrepreneurial initiative in San Diego that is part of Johnson & Johnson’s pharmaceutical business. “We have four or five medical systems. It would be great if we started working with those medical systems to make San Diego the city of the medical future, if we could really come together.”

The experts quickly identified a number of hurdles that must be overcome to realize this vision, including:

—Scalability. Smarr sees a challenge in developing a bioinformatics network that could expand from a pilot project to serve the health needs of a population as big as San Diego.

—Trustability. As a founding member of Google Health, which operated from 2008 to 2011, Missy Krasner said one issue that became a problem was who owns the data—and who would be the trusted custodian of the data? Krasner, who is now an entrepreneur-in-residence at Morgenthaler Ventures in Mountain View, CA, also asked why anyone would want to participate. “What are the incentives that get the average consumer and the average provider at Sharp or Scripps or anywhere else to actually want to receive that data and do something with it?”

—Profitability. “How do you make money?” asked Lisa Suennen, a co-founder and managing member of the Psilos Group, a healthcare-focused venture capital firm in Corte Madera, CA. “If there’s not a clear path to that, it’s a barrier.”

—Engagability. Generating meaningful feedback for patients will be a challenge, said Ernesto Ramirez, who is working at UCSD’s Center for Wireless and Population Health Systems on a doctorate in health behavior. “To me the issue is not the statistical methods that tell me whether I’m going to have a heart attack. It’s the layering on of all the behavioral methods, the visualization, and all the other ways that you can help me understand the data.”

Despite the thicket of difficulties, though, there are still some things that could be done—which was another recurring theme of the discussion.

“You just start,” said Mark Stevenson, the president and chief operating officer of Life Technologies (NASDAQ: LIFE), the global biotechnology company based in Carlsbad, CA. If Larry Smarr’s 10-year experiment in quantified health represents what Stevenson calls an “n of 1”—a single case study—then it’s simply a matter of trying to extrapolate the technology from there to get to an “n of 300,” or an “n of 3 million.”

Rather than trying to address everything, Stevenson said there are practical ways to collaborate by taking on tasks that could be more easily accomplished. For example, Stevenson said Life Technologies has provided its Ion Torrent genetic diagnostic tools to help develop individualized treatment regimens for a small group of 18 women in Phoenix, AZ, who were diagnosed with so-called “triple negative” breast cancer.

“For me, the tipping point starts in critical disease areas,” Stevenson said. “So, oncology patients, newborn children with neurological disorders, and infectious disease.”

Laura Shawver, an ovarian cancer survivor who founded the Clearity Foundation so molecular diagnostics could be used to help develop more personalized therapies for other ovarian cancer patients, embraced the idea.

“San Diego is very entrepreneurial,” said Shawver, who also is the CEO of San Francisco-based Cleave Biosciences. “We all live it. We all do it. The thing that really bothers me is when I hear somebody say personalized medicine is the way of the future. No! It’s here and now.” For cancer patients in particular, she added, “When your life is on the line, you’ll do whatever it takes.”

Eric Topol

Several participants agreed that getting most patients to “buy in” to a quantified health program would likely be problematic—and so is patient compliance.

“I have patients and I tell them to use a Fitbit or a BodyMedia armband or whatever, and they use it for three months and after that it just kind of fizzles,” said Eric Topol, the prominent San Diego cardiologist and director of the Scripps Translational Science Institute.

“It is going to require behavioral change, but we can’t fundamentally change behavior anytime soon,” said Rick Valencia, who oversees a host of wireless health initiatives as vice president and general manager of Qualcomm Life, a Qualcomm (NASDAQ: QCOM) subsidiary. “We have to offer experiences that people embrace, and I think the way you do that is by starting really, really simple.”

Topol also raised another key issue—cost—saying technology innovations almost invariably increase the cost of health care.

“I had a really interesting dinner last week with Bill Gates,” Topol said, “and I was shocked because he was questioning all this stuff. He was saying, ‘Show me where it’s going to cut costs.”

“The only thing that’s ever proven to save costs is something that’s been preventive—so things like vaccines and pap smears,” said Drew Senyei of San Diego’s Enterprise Partners Venture Capital. “Prevention is the only way we’re going to bring costs down.”

“The cost of being able to match a [person’s disease] to a drug is much less than the actual cost of the drug itself,” said Shawver. “And the most expensive drug is the one that doesn’t work. Often times people go from drug to drug to drug in a trial-and-error approach that adds a lot to costs. But it the past, the ability to gain [personalized genetic] information has not been cost-effective.”

The cost issue is important, but a pilot program that demonstrates the potential of quantified health could open the way for more ambitious efforts, said Peter Ellsworth, president of the Legler Benbough Foundation, a $35 million fund that awards grants to improve the quality of life of in San Diego. Ellsworth, who retired in 1996 after a 10-year reign as the CEO of Sharp Healthcare, says a successful demonstration also could help lower the competitive tensions between San Diego’s three rival health systems: Sharp, Scripps Health, and the UC San Diego Health System.

“If somebody is doing something and people like it, and there’s some publicity, pretty soon, the others will come along,” Ellsworth said. “I think the technology really does offer us something that we haven’t had before, because we’re going to be able to demonstrate things we were never able to do before.”

Rivalries between doctors and healthcare systems also could become less relevant as people generate more of their own health data from devices like Fitbit and BodyMedia, said Smarr. He estimates that 25 percent of all medical test data now resides outside the confines of health care systems, and that it is only going to increase. So now is the time to start thinking about the scale of quantified health and how it’s going to work.

“We’ve got to find a way to make your own data transportable, and we’ve got to have the legal reforms so that if your body generates the data, then you own it,” Smarr said. “You might want to license it to somebody else, but you own it. That’s not where we are today.

“I’ve seen so many of these digital transformations over and over again,” Smarr continued. “You go from a data-poor world to a data-rich world, and in the data-rich world your solutions are completely different than in the data-poor world and there’s no way to predict what it’s going to be like in the data-rich world or who’s going to be on first. That’s the way it works.

“Nobody would have thought that Steve Jobs would come up with a way to work file-sharing with the record industry. But he did. And now Apple is worth more than any corporation in the world. But you can’t predict that.

“The point is to start thinking,” Smarr said. “Go to the end of the rainbow. Assume that everybody has data like I do. I’ve got a disk drive from the Craig Venter Institute in Maryland with 35 billion bytes of information, which is the sequencing of all the bacteria in my gut. I sent a little vial of stool to them on dry ice and I got back 35 billion numbers. So start thinking. Everybody has got 35 billion numbers like this, which by the way is more than the human genome.

“I spend all my time thinking, ‘How do I work in a world of rich numbers?’—not ‘How do I keep it from happening?’ So get your mind around the fact that that’s what the whole population is going to be like that, and start looking for business solutions, and legal and ethical solutions in that data-rich world. Because by the time you can actually do anything, that will be the reality for everybody. For some of us, it already is.”

That’s Smarr’s vision of the world of quantified health. From his work as an astronomer to director of a supercomputer center to the Internet and CalIT2, Smarr says his career has always been built around exponentials.

In attendance at the Xconomy dinner—which was sponsored by Alexandria Real Estate Equities, the Latham & Watkins law firm, Ernst & Young, and the TriNet human resources firm—were John Blume of Applied Proteomics, Jon Cohen of Science magazine, David Nelson of Epic Sciences, Larry Smarr of CalIT2, Eric Topol of Scripps Health, Lisa Suennen of the Psilos Group, Drew Senyei of Enterprise Partners, Missy Krasner of Morgenthaler Ventures, Rick Valencia of Qualcomm Life, Peter Ellsworth of the Legler Benbough Foundation, Tom Watlington of Sotera Wireless, Mark Stevenson of Life Technologies, Diego Miralles of Janssen Healthcare Innovation, Laura Shawver of the Clearity Foundation and Cleave Biosciences, Ernsto Ramirez of UCSD’s Center for Wireless and Population Health Systems, Jason Moorhead of Alexandria Real Estate Equities, partners Steven Chinowsky and Barry Clarkson of Latham & Watkins, Doug Regnier and John Clift of Ernst & Young, Shannon Conway and Anthony Pedrotti of TriNet. Xconomy Associate Publisher Jim Edwards and Xconomy San Diego Editor Bruce V. Bigelow also were there.


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2 responses to “Big Data, Big Biology, and the ‘Tipping Point’ in Quantified Health”

  1. Abdallah Al-Hakim says:

    Great article and one that touches on a very important topic for Digital Health.

    Mount Sinai hospital in Toronto recently launched centre of personalized genomics and innovative medicine (CPGIM) which is aims to enables and promote the implementation of personalized health care approach to the diagnosis and treatment of hereditary diseases. The program aims to link the patients, physicians and researchers together to share date and disseminate information.

    It is all exciting work towards getting the most out of “big data” and “big biology”

    For more on CPGIM –